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データ分析基盤の変遷とデータレイクの作り方
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Ojima Hikaru
April 21, 2018
Technology
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1.9k
データ分析基盤の変遷とデータレイクの作り方
Battle Conference U30 #2018
Ojima Hikaru
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Transcript
L FG A
• S')1 0(6T • L>A9 XFLAG CDB=
!?NRK • GRD /%Q$7 • GRDO:>3GRD;<8H;C-,/ ACFM • P?/5#2(4&"Q 1+/GRDJPR • BIERN/ • @RIC. *6 / • GitHub: ojima-h 2
4 DAUKPI !
5
6 • • 2TB/day
30 → 1000
7 • 5
→ 100
− 8 S3
− 9 S3
− 10 Redshift
− 11
12 Data Lake Architecture
Data Lake " • -4,&$#!-4,+.' • -4,&% "%,(13*+)40&% !
(Schema on Read) • Data Lake -4,& DWH 24/$ $% 13
Data Lake 14 Hive Metastore
Hive Metastore 15
Hive " • Hadoop%(47-:.69!; • SQL ,*7&$S3 # HDFS !1:/
#1:/ & • ORC !3')83+:502& 16
Hive Metastore • S3/HDFS * "-SQL /1,&(.&0 (.&%)! •
,&(.& • * "- • * "-*#.+') • (.&%$.+ • 17
Hive Metastore • EMR ! Hive Metastore
! • • EMR 30 18
Hive Metastore • Hive Metastore MySQL
• Hive Metastore (HCatalog) server • EMR 5 19
Hive Metastore S3 20
Hive Metastore • ' • '"%
• 'ORC • '!&' ' !'#$$ 21
Hive Metastore • Hive Metastore S3 "
S3" !" 22
Hive Metastore * • "+$%- :>:>(*+ • 8C6*/,# •
3C;4' Hive DB / • Hive ).!% S3&*8C6/ • Hive &.( 8C6)-*@C@/ 23 3C;4 D=A49B<019?C2BBE 8C6579 8C6 Hive Database Table Partition S3 s3://BUCKET/warehouse/SERVICE.db/ s3://BUCKET/warehouse/SERVICE.db/TABLE/ s3://BUCKET/warehouse/SERVICE.db/TABLE/y=YYYY/m=MM/d=DD/
Hive Metastore • %)" &'&'%)" • &$#
! ( 24
Hive Metastore 1. Hive Metastore
25
Hive Metastore 1. Hive Metastore
2. 26
Hive Metastore 1. Hive Metastore
2. 3. Hive Metastore 27
Hive Metastore 1. Hive Metastore
2. 3. Hive Metastore 4. 28
Hive Metastore ! 1. ),(! $ Hive Metastore # 2.
),($'*, 3. Hive Metastore ! $ 4. ),($ &%+ $ "),($ 29
Hive Metastore 30
Hive Metastore • Hive Redshift "%!$%# • Redshift
COPY "%! csv+gzip • Hive "%! ORC • Redshift csv+gzip Hive ORC ⇒ Redshift Spectrum 31
Redshift Spectrum • Redshift S3(#$+ &%*" • ',)+
Hive Metastore ! Hive ',)+" 32 CREATE EXTERNAL SCHEMA schema_name FROM HIVE METASTORE DATABASE 'database_name’ URI 'hive_metastore_uri’;
Hive Metastore • Redshift Hive 33 INSERT
INTO ‘Redshift ’ SELECT … FROM ‘Hive ’ WHERE y=YYYY AND m=MM AND d=DD;
Hive Metastore • Redshift Spectrum
Hive Metastore • Spark SQL • Presto • Athena • Flink 34
Hive Metastore Hive Metastore S3 Hive,
Redshift Spectrum , Spark 35
36
($) • Hive Metastore '25103-$251.4/4& • Hive Metastore , $"
Data Lake , !$# 251&*251&%+$#! Hive Metastore , +$# Data Lake , "$#(!6 37
None